Optimizing planting density and nitrogen application to enhance profit and nitrogen use of summer maize in Huanghuaihai region of China

Abstract

Low planting density and irrational nitrogen (N) fertilization are two common practices in conventional cropping of smallholder maize production in Huanghuaihai region of China. A 2-year field experiment was carried out to study the effects of N application and planting density on maize phenology, dry matter accumulation, profit, yield, N uptake and efficiency indices. The experiments included three N application levels (120 kg ha−1, N1; 180 kg ha−1, N2; 240 kg ha−1, N3) and three planting densities (60,000 plants ha−1, D1; 75,000 plants ha−1, D2; 90,000 plants ha−1, D3). Increasing N input and planting density delayed the physiological maturity and enhanced dry matter accumulation. Comparing with the traditional N3 level, grain yield and profit were kept stable at N2 level and decreased at N1 level, partial factor productivity of applied N (PFPN) and nitrogen efficiency ratio (NER) were increased with the decreasing of N level. Comparing with the traditional D1 density, grain yield, profit and PFPN were increased at D2 density and then kept stable at D3 density, NER was kept stable at D2 density and then decreased at D3 density. Based on the predicted maximum profit, the optimal combinations of N application and planting density were 199 kg ha−1 and 81,081 plants ha−1 in 2017, and 205 kg ha−1 and 84,782 plants ha−1 in 2018. The two optimal combinations had an increase of 17.6% for grain yield, 39.8% for PEPN, 3.6% for NRE than the traditional N3D1 treatment. Therefore, an appropriate combination of increased planting density with reduced N application could enhance profit and nitrogen use of summer maize in Huanghuaihai region of China.

From a point to a range of optimum estimates for maize plant density and nitrogen rate recommendations

“…An additional learning relative to future research is the consistency in shape of response surfaces we observed across cases (Figure 6). If one could assume a relatively consistent shape of grain yield response to N rate and plant density, it should be possible to develop experimental approaches to estimate the joint response to plant density and N rate simultaneously with far fewer levels than a full factorial of five N rates and five plant densities (e.g., H. Zhang et al., 2022).…”

“…Although there are several published studies examining how N rate, or plant density, or hybrid affects corn yield and net returns, there are disproportionally fewer studies examining all factors together. Previous studies have documented plant density interactions with hybrid on grain yield (Brekke et al., 2011; Cox, 1996; Edwards, 2016; Farnham, 2001; Sarlangue et al., 2007), N rate interactions with hybrid on grain yield (Y. Chen et al., 2015; Shapiro & Wortmann, 2006; Woli et al., 2016) or N rate with plant density interaction on grain yield (H. Zhang et al., 2022). These studies indicated linear or quadratic responses to plant density and N rate to grain yield along with quadratic plateau responses of grain yield versus N rate across hybrids.…”

“…These studies have focused on crop physiology aspects and did not calculate optimum N rate and optimum plant densities as none of them had sufficient treatment levels to reproduce a continuous grain yield response to plant density × N rate (F. E. Miguez & Poffenbarger, 2022). Recently, H. Zhang et al (2022) determined economic optimum N rates and plant densities that maximize profits for summer maize in China using limited treatment levels for one hybrid. Overall, our knowledge of the combined effect of N rate and plant density and their interaction with hybrids on crop yield and net return remains relatively unexplored, especially in the US Corn Belt, a major maize production region.…”

“…Recently, H. Zhang et al. (2022) determined economic optimum N rates and plant densities that maximize profits for summer maize in China using limited treatment levels for one hybrid. Overall, our knowledge of the combined effect of N rate and plant density and their interaction with hybrids on crop yield and net return remains relatively unexplored, especially in the US Corn Belt, a major maize production region.…”

Optimizing Crop Selection and Production Planning in Agriculture: Applications of Linear Programming for Profit Maximization and Sustainability

“…Through the application of linear programming in agriculture (Mitlif, R. J., et al 2021), farmers can make informed decisions to maximize profits, minimize costs, and optimize resource usage (Lubna, et al 2022). It aids in identifying the most profitable crops to cultivate (Alotaibi, A., & Nadeem, F. 2021), determining the optimal planting areas, and allocating resources efficiently to achieve higher yields and profitability (Zhang, H., et al 2022).…”